{"id":"W2392612598","doi":"","title":"A research on relations between urban competitiveness and real estate in Toronto","year":2007,"lang":"en","type":"article","venue":"Urban Problems","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Real estate; Real estate development; Economic geography; Business; Estate; Chinese city; Urban planning; Regional science; Corporate Real Estate; Residential real estate; Economy; Geography; China; Finance; Economics; Civil engineering; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002061327,0.0001094418,0.0003207866,0.0003196996,0.0001316237,0.00004993258,0.0001393288,0.00009867757,0.0002246122],"category_scores_gemma":[0.00003129285,0.0001237646,0.00005638463,0.000254187,0.0001115817,0.0002005456,0.00004994644,0.0002016769,0.0002392233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005699507,"about_ca_system_score_gemma":0.00001951316,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03958396,"about_ca_topic_score_gemma":0.02022002,"domain_scores_codex":[0.9985978,0.0000342017,0.0005650898,0.0004041849,0.00004975627,0.0003489781],"domain_scores_gemma":[0.9992415,0.000276244,0.0001354443,0.0002032127,0.0000324206,0.0001111281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001294845,0.00003667866,0.665177,0.000008906189,0.00002305235,0.000002762177,0.0007211004,0.00007656789,0.000001667696,0.3325139,0.0002194813,0.001205836],"study_design_scores_gemma":[0.0004968804,0.0001304923,0.9252529,0.00003891666,0.000003759586,6.12937e-7,0.0004700465,0.0009426013,0.000005994589,0.01647633,0.05597304,0.0002084508],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6109352,0.0005936703,0.000720538,0.0004842219,0.00005107564,0.0002210931,0.00005225425,0.00001848559,0.3869235],"genre_scores_gemma":[0.9944312,0.0006335257,0.0001321191,0.00002893232,0.0001160844,0.00001904459,0.00003218228,0.00001668281,0.004590226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.383496,"threshold_uncertainty_score":0.9976584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07643573283564238,"score_gpt":0.3011690884896716,"score_spread":0.2247333556540292,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}